Certified NoSQL Analyst (MongoDB) (CNA)

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Transcript of Certified NoSQL Analyst (MongoDB) (CNA)

Page 1: Certified NoSQL Analyst (MongoDB) (CNA)

COPYRIGHT © GICT TRAINING & CERTIFICATION. ALL RIGHTS RESERVED.

Certified NoSQL Analyst (MongoDB) (CNA)

Course Outline

www.globalicttraining.com

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Certified NoSQL Analyst (MongoDB)

DURATION

5 Days

COURSE OBJECTIVES

Modern day businesses accumulate an astonishing amount of digital data, which can be leveraged

to unlock new sources of economic value or to provide fresh insights into business trends.

Business Analytics is the emerging and fastest growing technology which every organization is

embracing. Given the context of data growth both in structured and unstructured way, organization

also need to move forward from SQL to NoSQL technology to store and handle the data before

analyzing it. MongoDB is one of the new open source databases that focus on the ideas of the

NoSQL (Not Only SQL) approach.

This specialized course focuses on MongoDB to implement different ways to store and handle data

that can be modeled as a document format. This database is employed to handle documents in a

free schema design that provides great flexibility to store and use data. This course covers the

concept of big data, role of big data analytics in business, data/information architecture, data

warehousing, business intelligence, NoSQL approach, data mining techniques and NoSQL &

analytical tools and deals with the basic principles of MongoDB, key features, operations,

data model and MongoDB architecture. Participants will be explored from installation and

configuration of MongoDB to working on Mongo shell. Participants will learn data types in

MongoDB, its schema design, create-read-update-delete operations, other MongoDB operators and

index. In addition, participants will also learn about different data mining techniques through an

open source analytical tool RapidMiner.

Data Analyst - Statistics and Mining

Big Data Analyst

Database Administrator Data Scientist Operations Research Analyst

IHL Students

TARGET AUDIENCE

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PRE-REQUISITES

Participants are preferred to have some experience in software development with any RDBMS/

SQL database environment.

PROGRAM STRUCTURE

This is a 5-day intensive training program with the following assessment components.

Component 1. Written Examination

Component 2. Project Work Component (PWC)

These components are individual based. Participants will need to obtain 70% in both the components

in order to qualify for this certification. If the participant fails one of the components, they will not

pass the course and have to re-take that particular failed component. If they fail both components,

they will have to re-take the assessment.

COURSE OUTCOMES

Understand business analytics with its impact on enterprises

Understand the role of big data and NoSQL in business

Learn NoSQL concepts and technique through an open source tool

Acquire the knowledge and learn the design and operations of a NoSQL technology

(MongoDB)

Learn data mining concepts and techniques through an open source analytical tool

COURSE SESSION SCHEDULE

Day 1

Session 1

(9:00 – 10:30)

Session 2

(10:40 – 12:10)

Session 3

(13:10 – 16:10)

Session 4

(16:10 – 18:10)

Introduction to Business

Analytics

Introduction to Business

Analytics

Data/Information Architecture for

Business Analytics

Introduction to Big Data

Day 2

Session 1

(9:00 – 10:00)

Session 2

(10.10 – 12:10)

Session 3

(13:10 – 14:10) Session 4

(14:10 – 17:10) Session 5

(17:10 – 18:40)

Introduction to Big Data Introduction to NoSQL Introduction to NoSQL

Introduction to MongoDB

Installation of MongoDB

Day 3

Session 1

(9:00 – 10:30)

Session 2

(10:40 – 12:40)

Session 3

(13:40 – 14:10)

Session 4

(14:10 – 16:10)

Session 5

(16:10 – 18:10)

Installation of MongoDB Mongo Shell Mongo Shell

MongoDB Data Types

Schema Design

Day 4

Session 1

(9:00 – 10:30)

Session 2

(10:40 – 12:10)

Session 3

(13:10 – 16:10)

Session 4

(16:10 – 18:10)

CRUD Operations CRUD Operations MongoDB Operators

MongoDB Indexes

Day 5

Session 1

(9:00 – 10:00)

Session 2

(10:10 – 12:10)

Session 3

(13:10 – 15:10)

Session 4

(15:10 – 17:40)

MongoDB Indexes Data Mining Tool Data Mining Techniques

CNA examination

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COURSE OUTLINE

Unit 1: Introduction to Business Analytics

- The concept of Business Analytics

- Data, Information, Knowledge and Wisdom

- Data as Unique Enterprise Asset

- Data, Information and Analytics Lifecycle

- Business Analytics – Current Context

- Types of Analytics

o Descriptive Analytics

o Predictive Analytics

o Prescriptive Analytics

Unit 2: Data/Information Architecture for Business Analytics

- Data/Information Architecture

- Concept of Data Warehouse/Enterprise Data Warehouse (EDW)

- ETL – Key Process

- Concept of Data Mart

- Business Intelligence

- Data Mining

Unit 3: Introduction to Big Data

- What is Big Data? Why Big Data?

- 3V’s of Big Data

- The Rapid Growth of Unstructured Data

- Big Data Market Forecast

- Big Data Analytics

- Big Data in Business

- Big Data Types & Architecture

Unit 4: Introduction to NoSQL

- What is NoSQL

- Why is NoSQL

- Motives Behind NoSQL

- What is wrong with RDBMS?

- ACID Semantics

- CAP Semantics

- BASE

- Concurrency Models

- Data Models

o Key-Value Stores

o Tuples (rows)

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o Document Stores

o Object Stores

o Column Stores

o Graph Stores

Unit 5: Introduction to MongoDB

- MongoDB Data Model

- Deployment Architectures

- MongoDB Design Philosophy

- Key MongoDB Features

- Operations

- Data Model

- Other NoSQL Types

- JSON & BSON

- MongoDB Architecture

- Uses

Unit 6: Installation of MongoDB

- Install MongoDB On Windows

- Install MongoDB On Ubuntu

Unit 7: Mongo Shell

- Starting the Mongo Shell

- Core Options in Mongo Shell

- Command Helpers

- Basic Shell JavaScript Operations

- Execute a JavaScript file

Unit 8: MongoDB Data Types

- Data Types

- Comparison/Sort Order

- BSON Data Types

Unit 9: Schema Design

- Dynamic Schema

- Schema Considerations

- Data Manipulation

- Data Access

- Document Structure

- References

- Embedded Data

- Atomicity of Write Operations

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- Model Relationship between documents

- Model Specific Application Contexts

- Model Data to Support Keyword Search

- Limitations of Keyword Indexes

- Model Monetary Data

- Model Time Data

Unit 10: CRUD Operations

- Create Database

- Drop Database

- Create Collection

- Drop Collection

- Write Operation Overview

- Insert Behavior

- Update Document

- Read Operation Overview

- Query Interface

- Query Statement

- Remove Method

- Projections

Unit 11: MongoDB Operators

- Query and Projection Operators

- Update Operators

- Aggregation Pipeline Operators

Unit 12: MongoDB Indexes

- Creating Index

- Ensure Index

- Remove Index

- Index Information

- Index Types

Unit 13: Data Mining Tool

- Understand the open source DM tool RapidMiner

- Explore the various features of RapidMiner

- Walkthrough a RapidMiner demo with different scenarios

Unit 14: Data Mining Techniques

- Understand the various data mining techniques

- Understand how correlation matrix works

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- Understand how association rule mining works

- Understanding the Predictive Analytics technique

- Understand the forecasting technique

WRITTEN ASSESSMENT

As part of the written examination, each participant will be assessed individually on the last day of the

training for their understanding of the subject matter and ability to evaluate, choose and apply them

in specific context and also the ability to identify and manage risks. The assessment focuses on higher

levels of learning in Bloom’s taxonomy: Application, Analysis, Synthesis and Evaluation.

This written examination will primarily consist of 40 multiple choice questions spanning various

aspects as covered in the program. It is an individual, competency-based assessment.

EXAM PREPARATION

The objective of the certification examination is to evaluate the knowledge + skills acquired by the

participants during the course on Big Data. The weightage in key topics of the course as follows:

Introduction to Business Analytics [5]

Data/Information Architecture for Business Analytics [5]

Introduction to Big Data [5]

Introduction to NoSQL [5]

Introduction to MongoDB [5]

Mongo Shell [5]

MongoDB Data Types [10]

Schema Design [15]

CRUD Operations [15]

MongoDB Operators [10]

MongoDB Indexes [10]

Data Mining Tool & Techniques [10]

• MongoDB Compass• MongoDB• RapidMiner

TOOLS/SOFTWARE USED